Titlebook: Neural Connectomics Challenge; Demian Battaglia,Isabelle Guyon,Jordi Soriano Book 2017 Springer International Publishing AG 2017 Neuronal

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Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging,ts of two steps. First, processing the raw signals to detect neural peak activities. Second, inferring the degree of association between neurons from partial correlation statistics. This paper summarises the methodology that led us to win the Connectomics Challenge, proposes a simplified version of

被告

MEET

Signal Correlation Prediction Using Convolutional Neural Networks,ectiomics contest dataset of fluorescence imaging of neural activity recordings – the aim is reconstruction of the wiring between brain neurons. The model makes accurate predictions and took the fourth place in this contest. The performance is similar to the other leading solutions, thus we showed t

Ordeal

Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization,in the literature show that the Generalized Transfer Entropy (GTE), derived from information theory, has a great capability of reconstructing the underlying connectomics. In this work, we first generalize the GTE to a measure called Csiszár’s Transfer Entropy (CTE). With a proper choice of the conve

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Predicting Spiking Activities in DLS Neurons with Linear-Nonlinear-Poisson Model,he contrary, the functionality and physiology of the dorsolateral striatum (DLS), the immediate downstream region of M1 and S1 and a critical link in the motor circuit, still requires intensive investigation. In the current study, spike trains of individual DLS neurons were reconstructed using a Lin

ADORN

SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data,in the other dimensions. E.g. in electron microscopy it arises from the thickness of a scanned section. This leads to blurred images and raises problems in tasks like neuronal image segmentation. We present the details and additional evaluation of an approach originally introduced in Laptev et al. I

AUGER

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